In order to remove the influence of the aperture fill time (AFT) for wideband array, the scaling principle of the Keystone (KT) transform is applied to eliminate the linear coupling between spatial domain and frequency domain of wideband array signal. However, the classic KT transform is implemented by interpolation Sinc which is difficult to apply in engineering and leads to the serious problem of insufficient data. To address this, a realization of the low-complexity KT transform is presented, and it is implemented using only the Chirp-z transform (CZT) and fast Fourier transforms (FFT). Additionally, an Autoregressive (AR) model is proposed to compensate the insufficient data for each range, and the order of AR is estimated by the rank of the signal covariance matrix. Simulation results demonstrate that the proposed algorithm significantly reduces computational burden and improves the performance of wideband array beamforming.